How can i change the contrast at few locations in an image?

I want to lower the contrast at particular locations in an image but not the whole image. Is there any way to change it just by clicking some places on image and giving our desired grey color without specifying coordinate points??

Answer 1

[Image Analyst]

Somehow the "particular" locations must be specified, don't you agree? If you don't know the "coordinate points" of the areas to be included and excluded then you don't know what locations to reduce the contrast in, right?

You need to have a binary mask. Then filter the whole image, but replace the masked areas by the original. For example

mask = false(rows, columns); % Initialize
mask(1:rows/2,:) = true; % Mask top half of image.
% Now do your filtering on the whole image.

% Now replace top half with original image:
filteredImage(mask) = grayImage(mask);

[Image Analyst]

Divya says:

thanks for your response. I had issues implementing your solution.

First is when i use binary masking, the final result is a vector, which i had problem in reshaping into my original matrix.

Secondly, I don't want to specify any particular rows nor columns nor coordinate position. Because i have 100 images and each image has to be processed. So it is not reliable to specify coordinate positions and rows/columns for each image. I just want to click on the image and select so that for that particular region, i can make region to low contrast.

Is there any way to do that?? I think definitely there should be some good solution for this in matlab

[Image Analyst]

OK, so you click, using ginput(), but how does it know how far away from that single pixel the region extends? Two pixels away? In a circle shape, or a rectangle shape, or an irregular shape based on something like intensity or texture? How are you going to define the region based on just a single pixel?

[Divya]

Yeah.. it is not a single pixel. It is an irregular shape based on intensity values. I can't do it with ginput()

It is just like contrast adjustment on an image using imadjust, or histeq, or adapthisteq etc., these all functions does it on whole image. But i want to adjust only to a particular region of an image that i select.

[Divya]

""Somehow the "particular" locations must be specified, don't you agree? If you don't know the "coordinate points" of the areas to be included and excluded then you don't know what locations to reduce the contrast in, right?"" .... Yes, but what i want is just by clicking the image i want to select the region but not by specifying the coordinate position in the code itself..

Hope you got my question. Please let me know if not

[Image Analyst]

Select the region HOW!?!? Again, what criteria should be used to define "the region"? A click just specifies one pixel. Do you want to trace out an irregular area with imfreehand() instead of just clicking a single point? Or you want to click a bunch of points with roipolyold()? Or do you want something like Photoshop's Magic Wand? I need to know if I am to provide an answer to you.

[Divya]

Yeah Analyst, I am looking for function like "imfreehand()". Now i can change the contrast based on the region selected by imfreehand(). Thank you so much for your response. I will try it out with this. And sorry to mislead you by using the word "click" in my question.

[Image Analyst]

Divya, here's my demo for imfreehand():

% Demo to have the user freehand draw an irregular shape over
% a gray scale image, have it extract only that part to a new image,
% and to calculate the mean intensity value of the image within that shape.
% Also calculates the perimeter, centroid, and center of mass (weighted centroid).

% Change the current folder to the folder of this m-file.
if(~isdeployed)
  cd(fileparts(which(mfilename)));
end
clc;  % Clear command window.
clear;  % Delete all variables.
close all;  % Close all figure windows except those created by imtool.
imtool close all;  % Close all figure windows created by imtool.
workspace;  % Make sure the workspace panel is showing.
fontSize = 16;

% Read in a standard MATLAB gray scale demo image.
folder = fullfile(matlabroot, '\toolbox\images\imdemos');
baseFileName = 'cameraman.tif';
% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);
% Check if file exists.
if ~exist(fullFileName, 'file')
  % File doesn't exist -- didn't find it there.  Check the search path for it.
  fullFileName = baseFileName; % No path this time.
  if ~exist(fullFileName, 'file')
    % Still didn't find it.  Alert user.
    errorMessage = sprintf('Error: %s does not exist in the search path folders.', fullFileName);
    uiwait(warndlg(errorMessage));
    return;
  end
end
grayImage = imread(fullFileName);
imshow(grayImage, []);
axis on;
title('Original Grayscale Image', 'FontSize', fontSize);
set(gcf, 'Position', get(0,'Screensize')); % Maximize figure.
message = sprintf('Left click and hold to begin drawing.\nSimply lift the mouse button to finish');
uiwait(msgbox(message));
hFH = imfreehand();
% Create a binary image ("mask") from the ROI object.
binaryImage = hFH.createMask();
xy = hFH.getPosition;

% Now make it smaller so we can show more images.
subplot(2, 3, 1);
imshow(grayImage, []);
axis on;
drawnow;
title('Original Grayscale Image', 'FontSize', fontSize);

% Display the freehand mask.
subplot(2, 3, 2);
imshow(binaryImage);
axis on;
title('Binary mask of the region', 'FontSize', fontSize);

% Label the binary image and computer the centroid and center of mass.
labeledImage = bwlabel(binaryImage);
measurements = regionprops(binaryImage, grayImage, ...
    'area', 'Centroid', 'WeightedCentroid', 'Perimeter');
area = measurements.Area
centroid = measurements.Centroid
centerOfMass = measurements.WeightedCentroid
perimeter = measurements.Perimeter

% Calculate the area, in pixels, that they drew.
numberOfPixels1 = sum(binaryImage(:))
% Another way to calculate it that takes fractional pixels into account.
numberOfPixels2 = bwarea(binaryImage)

% Get coordinates of the boundary of the freehand drawn region.
structBoundaries = bwboundaries(binaryImage);
xy=structBoundaries{1}; % Get n by 2 array of x,y coordinates.
x = xy(:, 2); % Columns.
y = xy(:, 1); % Rows.
subplot(2, 3, 1); % Plot over original image.
hold on; % Don't blow away the image.
plot(x, y, 'LineWidth', 2);
drawnow; % Force it to draw immediately.

% Burn line into image by setting it to 255 wherever the mask is true.
burnedImage = grayImage;
burnedImage(binaryImage) = 255;
% Display the image with the mask "burned in."
subplot(2, 3, 3);
imshow(burnedImage);
axis on;
caption = sprintf('New image with\nmask burned into image');
title(caption, 'FontSize', fontSize);

% Mask the image and display it.
% Will keep only the part of the image that's inside the mask, zero outside mask.
blackMaskedImage = grayImage;
blackMaskedImage(~binaryImage) = 0;
subplot(2, 3, 4);
imshow(blackMaskedImage);
axis on;
title('Masked Outside Region', 'FontSize', fontSize);
% Calculate the mean
meanGL = mean(blackMaskedImage(binaryImage));

% Put up crosses at the centriod and center of mass
hold on;
plot(centroid(1), centroid(2), 'r+', 'MarkerSize', 30, 'LineWidth', 2);
plot(centerOfMass(1), centerOfMass(2), 'g+', 'MarkerSize', 20, 'LineWidth', 2);

% Now do the same but blacken inside the region.
insideMasked = grayImage;
insideMasked(binaryImage) = 0;
subplot(2, 3, 5);
imshow(insideMasked);
axis on;
title('Masked Inside Region', 'FontSize', fontSize);

% Now crop the image.
leftColumn = min(x);
rightColumn = max(x);
topLine = min(y);
bottomLine = max(y);
width = rightColumn - leftColumn + 1;
height = bottomLine - topLine + 1;
croppedImage = imcrop(blackMaskedImage, [leftColumn, topLine, width, height]);
% Display cropped image.
subplot(2, 3, 6);
imshow(croppedImage);
axis on;
title('Cropped Image', 'FontSize', fontSize);

% Put up crosses at the centriod and center of mass
hold on;
plot(centroid(1)-leftColumn, centroid(2)-topLine, 'r+', 'MarkerSize', 30, 'LineWidth', 2);
plot(centerOfMass(1)-leftColumn, centerOfMass(2)-topLine, 'g+', 'MarkerSize', 20, 'LineWidth', 2);

% Report results.
message = sprintf('Mean value within drawn area = %.3f\nNumber of pixels = %d\nArea in pixels = %.2f\nperimeter = %.2f\nCentroid at (x,y) = (%.1f, %.1f)\nCenter of Mass at (x,y) = (%.1f, %.1f)\nRed crosshairs at centroid.\nGreen crosshairs at center of mass.', ...
meanGL, numberOfPixels1, numberOfPixels2, perimeter, ...
centroid(1), centroid(2), centerOfMass(1), centerOfMass(2));
msgbox(message);

[Divya]

Thank you. This would be useful